A Study on the Collaborative Approach of Tailored Policies and Technology Empowerment for Plateau Specialty Agriculture Bases in Yuxi City

Sustainable Development Re search; V ol. 8, No. 2; 2026
ISSN 2690-9898 E - I S S N 2 6 9 0 -9901
https://doi.org/10.30560/sdr.v8n2p47
4 7 P u b l i s h e d b y I D E A S S P R E A D

A Study on the Collaborative Approach of Tailored Policies and
Technology Empowerment for Plateau Specialty Agriculture Bases in
Yuxi City
Zefeng Li1 , Tianyong Xu1, Huiqing Xu1 & Hongli Li1
1 Yuxi Agricultural Vocational and Technical College, China
Correspondence: Tianyong Xu, Yuxi Agricultural Vocational and T echnical College, China. E-mail:
[email protected]

Received: October 1, 2026 Accepted: October 25, 2026 O n l i n e P u b l i s h e d : O c t o b e r 2 7 , 2026

This work was supported by the Yuxi Science and Technology Plan Self-funded Project (No. 2026ZC10),
“Research on Pathways for Enhancing the Quality and Efficiency of Yuxi Plateau Characteristic
Agricultural Bases through Science and Technology Empowerment”, and the Yuxi Federation of Social
Sciences Project (No. Yxsk2026127), “Research on Bottlenecks and Countermeasures for the Development
of Cross-border E-commerce Export of Plateau Characteristic Agricultural Products in Yuxi City.”

Abstract
Grade-based and category-specific management of agricultural bases, combined with tech empowerment, are two
main approaches to improving the quality and efficiency of plat eau agriculture. However, in practice, these two
have long operated independently according to their own logics. The classification standards focus more on static
conditions, and tech support often lacks scenario adaptation, leading to a structural mismatch between “recognized
bases” and “empowered bases.” This paper develops an analysis f ramework of “classification identification—
technology matching—collaborative governance,” using the provin cial, municipal, and county-level base
recognition system in Yuxi City along with tech support in faci lity agriculture, seed industry, technology
commissioners, and digital agriculture as case studies. It exam ines how classification-based measures and tech
empowerment are coupled. The study finds that Yuxi has established a classification system with “ten standards”
for quantitative recognition and three-tier dynamic management, while tech support covers facilities and
equipment, seed breeding, promotion services, digital platforms , and processing/cold chains, with some bases
already showing a preliminary coupling of “high facilities—high output—high drive”. However, the recognition
standards fall short in identifying the need for tech upgrades, there’s a mismatch between tech supply and base
types, county-level bases have weak capacity to utilize tech, and tech penetration in farmer linkages is insufficient,
creating four main obstacles to coordinated progress. Based on this, the paper proposes solutions like tiered precise
empowerment, type-specific techno logy routes, joint review and conduction by dispatched teams, linking tech
indicators to rewards instead of subsidies, and dynamic monitoring via digital platforms, providing a reference for
turning highland agricultural bases from just “recognized” to “technologically empowered”.
Keywords: Plateau-specific agriculture, ag ricultural industry base, targe ted policies, tech empowerment,
collaborative approaches

1. Introduction
   Agricultural industry bases are the spatial carriers for the sh ift of highland specialty agriculture from a “product-
   oriented” mindset to an “industry-oriented” one. In recent years, Yunnan has developed a tiered and categorized
   recognition and management system around initiatives like “one county, one industry”, modern agricultural
   industrial parks, and industry base construction. Building on t his, in 2023, Yuxi City introduced the
   “Implementation Plan for Accelerating the Construction of Moder n Agricultural Industry Bases”, building bases
   in tiers and categories at the provincial, municipal, and county levels. The plan uses the “Ten Standards” to quantify
   scoring and is supported with reward-based funding. Meanwhile, technological supply in areas like facility
   agriculture, quality seed breeding, agricultural science officers, and digital agriculture continues to deepen. Cases
   like facility-grown blueberries, smart greenhouse flowers, and long-season peppers show that technology
   significantly improves yield per hectare, quality, and production seasons.

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However, the two main tracks have not naturally converged. Base recognition standards measure “whether the
current standard is met”, while technological empowerment addre sses “how to upgrade in the future”. Classified
management tends to fit bases into a predetermined tier framework, whereas technology promotion tends to push
mature technologies to all promotable targets. Fang Chuanglin ( 2025), discussing classified measures in urban-
rural integration, points out that such measures need to be “ad apted to category, locality, timing, characteristics,
and degree”, with the core being to identify differences rather than rank levels [1]. Deng Yue and Wu Yujie (2026),
from a four-dimensional perspectiv e of “technological breakthro ugh–factor reorganization–organizational
innovation–institutional adaptation”, note that technological breakthroughs do not automatically enhance industry-
level productivity. Only when new and traditional factors form effective combinations and receive supporting
institutions can technological achievements reliably translate into real productivity [2].
These studies reveal the deep logic behind classified measures and technological empowerment, respectively, but
they still do not answer a key question: under an already estab lished tiered and classified management system,
how can technological empowerment match base levels, industry t ypes, and the capacities of operating entities?
And how can classified measures provide signals for technology resource allocation based on demand?
Previous studies have provided three directions of findings for this issue. In terms of base classification
management, Zhao Haiyan et al. (2024) evaluated modern agricult ural parks from four dimensions: element
agglomeration, industrial chain agglomeration, functional agglomeration, and driving agglomeration, pointing out
that industrial chain agglomeration is the most prominent limiting factor[3]; Huo Ming et al. (2026) measured the
coupling coordination level of “agricultural upgrading–rural progress–farmer development” based on monitoring
data from agricultural science parks, offering an indicator-based model for park classification evaluation[4]; Zhou
Tingting et al. (2024), using Qitang Town in Bishan District, Chongqing as an example, divided eight villages into
four types: comprehensive development, dominant development, polarized development, and underdeveloped, and
proposed targeted differentiated construction paths, providing a typological method reference for base
classification[5].
Regarding technology empowerment and technology diffusion, Tong Dajian et al. (2018) confirmed that grassroots
public agricultural technology promotion significantly facilita tes farmers' technology adoption [6]; Rogers (2002)
innovation diffusion theory and Feder et al. (1985) review of t echnology adoption provide an analytical tool of
“relative advantage–compatibility–complexity–trialability–observability”[7]; Chen Qiong et al. (2026), using the
Henan Academy of Agricultural Sciences as an example, summarize d three types of technology empowerment
models: intensive use of technological innovation resources, te chnology-led quality and efficiency improvement
of characteristic industries, and technology-supported integrat ion of agriculture, culture, and tourism [8]; Sun
Guofan (2026) discussed the paths for new quality productivity to empower agricultural technology promotion,
including improving the promotion service system, strengthening technology innovation transformation,
advancing digital agricultural services, and cultivating grassroots agricultural technology talents[9].
In terms of plateau characteristic agriculture, Du and Zhang (2 024) constructed a theoretical framework for
ecological safety supervision of plateau characteristic agricul ture[10], Wang et al. (2024) identified influencing
factors for sustainable development of Yunnan’s plateau charact eristic agriculture using a DEMATEL-AISM
combined model[11], and Ye et al. (2025) discussed the relationship between produ ction methods of Yunnan’s
plateau characteristic agriculture and food safety from the perspective of ecological economy[12].
For industrial chain coordination, Jiang Changyun (2016) sugges ted that the focus of the integration of primary,
secondary, and tertiary industries lies in improving profit connection mechanisms, building innovation platforms,
and innovating service industry systems[13]; Cai Jie et al. (2025), from a s ymbiosis perspective, summarized four
main mechanisms through which 'chain-leading' enterprises link and support farmers: industrial chain extension,
supply chain optimization, value chain enhancement, and profit chain connection[14].
The studies above address questions like “how to classify and e valuate bases,” “how technology spreads,” and
“how highland specialty agriculture can develop sustainably,” but they rarely look at how policy classification and
tech empowerment interact within the same framework. If base cl assification only serves identification and
certification, and tech empowerment only aims at increasing tec h coverage, neither can fully explain the
differences in improving base quality and efficiency on their o wn. This article tries to answer: given an already
established tiered and classified management system, how can tech empowerment align with base level, industry
type, and the capacity of operators, and how can policy classif ication send signals for tech resource allocation?
Using experience from Yuxi City, this paper builds a “classific ation recognition—technology matching—
collaborative governance” framework to analyze the practical progress, current challenges, and ways forward for
this coordination.

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2. Analysis Framework: Classification Identification, Technology Matching, and Collaborative Governance
   (1) Classification Identification: The Signal Function of Grading and Classifying Bases
   The management significance of grading and classifying bases li es in “recognizing differences” rather than just
   “ranking levels”(see Figure 1). Fang Chuanglin (2025), when dis cussing differentiated policies for urban-rural
   integration, proposed five principles: “adapt to the category, adapt to the place, adapt to the time, adapt to the
   specifics, and adapt to the extent” [1]. The core insight here is that classification standards should reflect the
   development stage, resource endowment, and functional positioni ng of the target, rather than just a single
   dimension like scale or output. Zhou Tingting et al. (2024), in evaluating livable and business-friendly beautiful
   villages, divided villages into four types—comprehensive develo pment, dominant development, polarized
   development, and underdeveloped—based on strengths and weakness es. This shows that classification
   identification only generates practical policy signals when combined with “shortcoming identification”[15].

Figure 1. Analytical framework for the coordinated advancement of differentiated strategies and technology
empowerment of highland-characteristic agricultural bases in Yuxi City

Specialty Agriculture Bases Yuxi's three-tier system is based on the “Ten Criteria” for scoring—operating entity,
appropriate scale, production standards, target market, quality assurance, brand leadership, modern facilities,
professional services, higher output, and farmer linkage. Count ies scoring above 60 are recognized at the county
level, cities above 80 at the city level, and provincial-level candidates are selected from city-level entries (Note 1).
This setup actually contains two types of information: one is b asic conditions (entity, scale, standards, market),
and the other is upgrade capacity (quality, brand, facilities, services, output, driving force). The former determines
whether the base “can stand on its own”, while the latter deter mines where the base “can go”. The quality of
classification depends on two conditions: first, whether the standards can differentiate the technical requirements
of the base, not just scale and industry type; second, whether dynamic management after recognition can
continuously drive upgrades. The Yuxi plan clearly sets up a base creation database, a county-level base database,
and a city-level base database, implementing dynamic management; if negative indicators appear, the designation
is revoked, which provides a system basis for classification. B ut in the “Ten Criteria”, indicators like “modern
facilities” and “professional services” lean more on existing conditions and have limited ability to identify which
stage of the technical life cycle a base is in or what kind of technology it needs next.
(2) Technology Matching: The Logic of Scene Adaptation for Tech Empowerment
Tech empowerment isn't just a simple stack of technical element s—it's a process of matching technology to the
site context. Rogers (2002) pointed out that the adoption speed of innovations depends on relative advantage,
compatibility, complexity, trialability, and observability [6]; Feder et al. (1985) further emphasized that farmers'

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adoption of technology is jointly constrained by factor endowme nts, risk preferences, and institutional
environments[7]. Deng Yue and Wu Yujie (2026) categorize technological empowerment in smart agriculture into
operational, system, and paradigm levels: the operational level is the replacement of traditional tasks with specific
technologies, the system level is the integration of technologi es across different stages, and the paradigm level
involves system-wide adjustments in factor allocation, division of labor, and operational rules after technology
enters the production system[2]. This hierarchy directly informs base classification: different levels of bases require
different levels of tech empowerme nt. Provincial-level bases sh ould demonstrate system- and paradigm-level
technologies, city-level bases should handle system-level techn ology integration, and county-level bases should
focus on the application of operational-level technologies.
Chen Qiong et al. (2026) summarized three types of tech empower ment models from practices at the Henan
Academy of Agricultural Sciences : intensive use of technologica l innovation resources, boosting quality and
efficiency of specialty industrie s through tech leadership, and supporting the integration of agriculture, culture,
and tourism with technology. This shows that tech empowerment n eeds to be tailored to the type of industry and
the function of the base, rather than applying a “one-size-fits-all” approach[8]. Sun Guofan (2026) pointed out that
new productive forces empowering agricultural technology promot ion face practical challenges, such as an
incomplete promotion service system, poor tech innovation conve rsion, shortage of grassroots agricultural tech
talent, and farmers' limited ability to adopt technology. These issues are especially pronounced at the county-level
bases[9].
For the bases, technology matching involves at least three dime nsions: facility matching (whether smart
greenhouses, integrated water and fertilizer systems, and IoT a re suitable for the type and scale of the industry),
organizational matching (whether the technology is adopted by c ompanies, cooperatives, or public promotion
agencies), and chain matching (wh ether the technology is applie d at the production stage or post-harvest,
processing, and distribution stages). Yuxi's tech supply has de veloped five dimensions: facilities and equipment
(multi-span plastic greenhouses , fully substrate-based off-grou nd cultivation, integrated water and fertilizer
systems, PLC environmental control), seed breeding (provincial crop germplasm resources Yuxi bank, rose
germplasm nursery, virus-free strawberry seedlings), promotion services (1,271 tech commissioners, 9 provincial
tech promotion teams, 13,000 mu of demonstration bases), digital platforms (flower big data, smart citrus farming,
agricultural product traceability), and processing & cold chain (pre-cooling in the field, cold chain collection &
distribution centers, ready-to-eat vegetable processing). The complexity, investment threshold, and payback period
vary greatly across these five dimensions. If technologies are pushed to all bases without differentiation, it will
lead to situations like “high-spec underused” or “low-spec hard to use”.
(3) Collaborative Governance: Triple Matching of the Base as a Coupling Interface
Classification identification provides the “demand signals”, an d technology matching offers the “supply
solutions”. Both need to achieve triple matching on the base as the spatial carrier: hierarchy matching (provincial
bases take on leading technology demonstrations, municipal base s handle integrated technology promotion, and
county bases focus on applicable technology dissemination), type matching (different technology routes for facility
vegetables and fruits, open-field vegetables, flowers, livestoc k and poultry, and processing and circulation), and
subject matching (leading enterpr ises, cooperatives, family far ms, and small farmers ha ve varying capacities to
adopt technologies).
The key to collaborative governance isn't that the government handles all the matching, but rather in setting up the
institutional interfaces that make matching possible. Jin Lifu and Zhang Yuan (2026) pointed out when discussing
how new productive forces enable agricultural modernization tha t there are current challenges like insufficient
technological innovation capacity, obvious contradictions betwe en talent supply and demand, constraints on
industrial transformation, and imperfect policy systems—basically a “capable but not yet effective” situation. They
suggest continuous optimization in technology, talent, industry , and policy mechanisms[16]. Ma Defu and Yang
Bohan (2026) further highlight that enabling agricultural and rural modernization with new productive forces faces
real obstacles like gaps in infrastructure and technology appli cation, talent shortages and skill gaps, shallow
integration of scientific achievements with industrial chains, and incomplete institutional and policy support
systems. They stress the urgency of driving deep integration of technology and industry through scenario-driven
approaches and optimizing governance and policy supply through institutional innovation[17]. These insights are
directly relevant to applying differentiated policies for farml and bases and collaborative tech empowerment: the
project review mechanism links tech department project resources with the agricultural base database; tech expert
teams provide specialized services at the base level; performan ce-based incentives integrate tech indicators into
reward conditions; and digital platforms dynamically monitor technical needs and extension resources of the bases.
Based on this, the analytical framework of this paper can be summarized as: classify and identify demand signals

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→ match technology to form supply solutions → establish institutional interfaces via collaborative governance →
improve base quality and efficiency.
3. Progress in Yuxi City's Practice of Classified Policy Implementation and Technology Empowerment for
Bases
(1) Basic Formation of a Graded and Classified Management System
In 2023, Yuxi City issued the "Implementation Plan for Accelera ting the Construction of Modern Agricultural
Industry Bases," establishing the approach of “industrial base- oriented, base park-oriented, park standardization,
and processing agglomeration”. The construction is divided into three levels: provincial, municipal, and county,
with the goal of recognizing 200 municipal-level bases and 1,000 county-level bases by 2023, and striving to build
5,000 bases covering different industry types and development l evels by 2025. Recognition is quantified by the
“Ten-Standard Criteria”, scored out of 100, with county-level b ases required to score above 60 and municipal-
level bases above 80. From 2023 to 2025, the municipal finance will allocate 20 million yuan each year, following
a “build first, then subsidize; rewards instead of subsidies” a pproach specifically for base construction. Dynamic
management is established with creation databases at the county and municipal levels, and any negative indicators
will lead to the withdrawal of recognition.
Looking at the first batch of city-level base lists, the 278 bases cover 105 for fruits, 59 for flowers, 26 for pigs, 24
for vegetables, 12 for Chinese medicinal materials, 12 for poultry, 7 for edible fungi, 6 for flue-cured tobacco, and
6 for grains. The county distribution is 51 in Jiangchuan, 40 in Xinping, 36 in Chengjiang, 34 in Y uanjiang, 30 in
Hongta, 29 in Yimen, 24 in Eshan, 19 in Huaning, and 16 in Tonghai. This structure shows that the bases are now
classified into recognizable spatial patterns along the dimensi ons of “industry type” and “county distribution”,
providing a basic sample for the differentiated allocation of tech resources. At the county level, Jiangchuan's two
batches of district-level base lists are divided into planting, processing, and breeding industries. Yimen County has
67 proposed bases mainly in planting and breeding. Tonghai County's 39 demonstration bases are scored based on
the “five-have” standards: having an operating entity, having an appropriate scale, having standardized production,
having a target market, and having facility support. Scores ran ge from 76 to 97, showing the internal capacity
differences among county-level bases.
From the theoretical perspective of categorized policymaking, Yuxi's practice is inherently consistent with Fang
Chuanglin's (2025) idea of “tailoring policies by type and exte nt”[1]: industry types correspond to “by type”,
recognition levels to “by extent”, and county-level distribution to “by location”. However, “by timing” (technology
lifecycle stage) and “by special features” (base functional cha racteristics) are not well reflected in the current
standards, which is actually one of the coordination challenges we’ll discuss later.
(2) Technology Empowerment Creates Five-Dimensional Supply Capacity
In terms of facilities and equipment, Yuxi's facility agriculture area is expected to reach 752,000 mu by 2025, an
increase of 253,300 mu compared to 2021. Typical cases include Eshan Rongrong Agriculture's 80,000-square-
meter connected-film greenhouse, equipped with reverse osmosis water purification, integrated water and fertilizer
systems, and intelligent greenhouse environmental controls. The yield of bell peppers and chili peppers is 15–18
tons per mu, more than five times that of traditional planting, with a growing season extended by 4 months. The
280-mu base achieves annual sales exceeding 30 million yuan, and by 2025 it will be recognized as a "vegetable
basket" base in the Guangdong-Hong Kong-Macao Greater Bay Area. In Chengjiang, blueberries are grown using
full substrate off-ground cultiva tion, integrated drip irrigati on with water and fertilizer, and smart temperature-
controlled greenhouses, with a facility area of about 21,000 mu , and total output value expected to exceed 2.3
billion yuan by 2025. In Jiangchuan, Lǜjǔlóng butterfly orchids are grown in intelligent greenhouses equipped
with PLC automatic heating and fully automated water-fertilizer integration, with temperature fluctuations
controlled within 1°C, producing over 10 million seedlings annually.
In terms of quality seed breeding, Yunnan Province's provincial crop germplasm resource Yuxi Bank has built a
45-cubic-meter low-temperature seed storage facility and a 1,46 4-square-meter rose germplasm nursery. By
September 2025, it had preserved 9,865 germplasm resources, col lected and introduced 6,823, identified 8,866,
created 5,369 breeding materials, and cultivated 57 new varieties. Tonghai Jinhai Rose Seed Industry has collected
and introduced over 1,800 varieties and has been listed as a pr ovincial-level seed industry base. Jiangchuan Jiuxi
Strawberry has developed and authorized 10 new virus-free varieties and provides an average of 1.5 million virus-
free seedlings annually.
In terms of digital platforms, t he Hongta District Flower Big D ata Intelligent Supervision Platform has made
production smarter, management more data-driven, and operations more networked. Huaning is promoting smart

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agriculture for citrus with plant protection drones for aerial spraying, rail-mounted underground vehicles, and
micro-mist pesticide spraying. The Yuxi National Agricultural S cience and Technology Park has built over 190
innovation platforms, 10 science and technology achievement tra nsformation centers, and 199 agricultural
technology service and promotion organizations.
On the processing and cold chain side, Tonghai County's 714 cold storage units can now handle over 10,000 tons
of vegetables per day. The Central Y unnan Green Agricultural Products Industrial Park hosts 106 market entities,
with vegetable sales reaching around 750,000 tons in 2024 and output value exceeding 3.5 billion yuan. Yuanjiang
and Xinping continue to build cold chain storage centers, leveraging the China-Laos Railway cross-border logistics
industrial park and Xinping County's smart agricultural cold chain logistics park.
From the perspective of Deng Yue and Wu Yujie's (2026) framework of operation layer—system layer—paradigm
layer, Yuxi's facilities and equipment, as well as high-quality seed breeding, mostly fall under operation layer
empowerment. The digital platforms and processing cold chains are starting to touch the system layer, but cross-
link integration is still lacking. Paradigm layer empowerment—t hat is, the systematic adjustments in factor
allocation, division of labor, and operating rules after technology enters the production system—is still in its early
stages. This basically aligns with their view that nationwide, agricultural tech is still mainly empowered at the
operation layer, system layer empowerment has begun in some scenarios, but cross-link integration is insufficient
[2].
(3) Classification and technology have formed an initial coupling in some bases
From the experience, bases with higher classification levels of ten also have higher technology element density.
The Chengjiang blueberry base is not only listed as a city-leve l fruit base but also one of the categories with the
highest level of facility and digitalization. Its “315” model connecting farmers (tenants pay at least 15% cash rent,
companies take a 15% service fee from total revenue, and villag e collectives charge 1.5 yuan per kilogram
management fee) links technological benefits with farmer participation. Rongrong Agriculture is both a city-level
vegetable base and a “vegetable basket” base in the Greater Bay Area, with its Dutch-style greenhouse technology
input forming a closed loop with the export market. The Tonghai vegetable base cluster relies on technology task
forces and cold chain facilities to create a “technology–base–e xport” chain. These examples suggest that
classification recognition and technological empowerment have a potential for spontaneous coupling in high-level
bases.
But this kind of coupling is more “spot-based” rather than “sys temic”. Most county-level bases still focus on
individual technologies, and the integration between facilities , high-quality seeds, extension services, digital
technology, and cold chains is low. Dynamic management after classification hasn't yet formed a stable interface
with the follow-up support of science and technology projects, and there's also no clear rule linking the coverage
of science and technology task forces with the base levels. Thi s is where the difficulties in collaborative
advancement lie.
4. The Real Challenges Facing Coordinated Progress
(1) Evaluation criteria focus too much on static conditions, wi th insufficient recognition of technology iteration
needs
The “ten standards” — operating entity, appropriate scale, prod uction norms, target market, quality assurance,
brand leadership, modern facilities, professional services, hig h output, and farmer collaboration mechanisms —
mostly measure what a base 'already has' rather than “what it needs next”. A base might score 80 points and enter
the municipal-level list because of its existing facilities and scale, but its real technical bottleneck could be in post-
harvest processing or digital management, something the evaluat ion score doesn’t reveal. The first batch of
municipal-level proposed recognition in 2024 simplified the sta ndards to the “five haves” (having an operating
entity, appropriate scale, production norms, target market, and facilities), further emphasizing basic conditions
while paying even less attention to identifying the direction for technological upgrades.
Fang Chuanglin (2025) stressed that targeted policies need to be “adapted to the times and promoted in stages”[1],
and Zhou Tingting et al. (2024) also based their classification method on ‘strengths and weaknesses’ rather than a
single score[15]. In contrast, the current standards in Yuxi lack recognition of the technological lifecycle stages of
the bases and haven’t established a systematic output of a “tec hnology demand list”. If classification and
identification don’t produce a “technology demand list”, tech s upport can only be pushed according to a general
catalog, making it hard to be precise.
(2) Mismatch between tech supply and base types, with both “high-end but underutilized” and “low-end but hard
to use” coexisting

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The distribution of technological supply in Y uxi is uneven across different industries and levels. Capital-intensive
technologies like facility blueberries, smart greenhouse flower s , a n d l o n g - s e a s o n p e p p e r s a r e c o n c e n t r a t e d i n
leading enterprise bases in places like Chengjiang, Jiangchuan, and Eshan, with high investment thresholds and
long payback periods, making them hard for ordinary county-leve l bases and small to medium operators to
replicate. On the other hand, bases for open-field vegetables, mountain orchards, and livestock and poultry farming
might need low-cost green pest co ntrol, water-saving irrigation , disease purification, and simple cold chain
technologies, but the supply of these is relatively insufficien t. The scoring table for 39 demonstration bases in
Tonghai shows that facility support scores range from 8 to 15, with some bases clearly weak in “having facility
support”. Yet current tech projects tend to support high-end fa cilities that “add beauty to what's already there”
rather than basic upgrades that “provide help in tough times”.
Cao Yanxiong and Liu Qixin (2026) pointed out that smart agricu lture enabling new-quality agricultural
productivity faces challenges like insufficient core technology and system coordination, lagging development of
new types of agricultural operators, imperfect supporting polic y systems, and poor coordination between
technology use and agricultural ecology. In Yuxi, the 'insuffic ient core technology and system coordination' is
reflected in the low integratio n between facilities, high-quali ty seeds, digital tools, and cold chains, while the
“lagging development of new agricultural operators” shows up in county-level bases and small-to-medium
operators having limited ability to adopt high-tech equipment [18]. Wang Ying (2026), when discussing AI-powered
large-scale agriculture, also noted that large-scale agricultur al operators face strong constraints on technology
adoption costs and AI solution adaptability, which matches well with the Yuxi county-level bases' situation of both
“high-tech but underused” and “low-tech and hard to use” [19].
(3) Weak Science and Technology R eception Capacity at County-Le vel Bases, Hindering the “Last Mile” of
Promotion
County-level bases are the most numerous and widely distributed, but they are the weakest link in terms of science
and technology reception capacity. In Yuxi, 2,919 county-level bases and 874 city-level bases were newly
recognized in 2024, bringing the total to 4,317 county-level an d 1,152 city-level bases, with county-level bases
making up the vast majority. However, there is still a shortage of agricultural technicians in the counties, training
coverage for new business entities is insufficient, and some small and medium-sized farmers still rely on traditional
methods. The issue pointed out by Sun Mingyang (2021) that “public welfare services deviate from the real needs
of farmers, and the agricultural input distribution system dominates technology”[20] also exists in Yuxi County: the
service radius of science and technology envoys and special tea ms is limited. Nine special teams with more than
200 experts cannot cover over 4,000 county-level bases. The 1,2 71 science and technology envoys may seem
substantial, but once spread across all counties and industries, each envoy still has to serve a relatively large number
of bases. The technological needs of county-level bases often appear “small, scattered, and miscellaneous,” which
doesn’t perfectly match the special teams’ service approach of being organized by industry clusters.
Sun Guofan (2026), from the perspective of the promotion system, pointed out that empowering agriculture with
new quality productivity requires “improving the promotion serv ice system, strengthening the transformation of
agricultural scientific and technological innovations, advancin g digital agricultural technology services,
cultivating grassroots agricultural technology talents, and enhancing farmers' ability to adopt technology” [9]. These
five tasks all have varying degrees of shortcomings at the Yuxi county-level base. Ma Defu and Y ang Bohang
(2026) listed “talent shortages and capability gaps” as one of the main obstacles to empowering modern agriculture
and rural areas with new quality productivity, emphasizing the urgent need to “combine training and recruitment
to build a new type of farmer team that loves agriculture, understands technology, and is good at management” [17].
The issue of county-level bases' capacity to absorb technology essentially reflects a structural imbalance between
the end capabilities of the promotion system and the expansion of base numbers.
(4) Insufficient penetration of technology in farmer-linked initiatives, and uneven distribution of efficiency gains
The ultimate test of improving the quality and efficiency of bases is whether farmers earn more. Yuxi has already
developed farmer-linked models like the Chengjiang blueberry “3 15” and Xinping citrus “125”, but the
technological content of these models is mainly in the producti on stage. Farmers still mainly participate through
land rent and labor wages, while higher-level linkages such as technical management, order-based empowerment,
and brand premium have limited coverage. The tech task force ha s helped over 2,000 households, which is still
quite small compared to the city's hundreds of thousands of farmers. Tech experts have promoted farmers' income
by 150 million yuan, but spread across the households involved, the income increase effect still needs a more
detailed assessment.
Han Guihua (2026) explains the mechanism of how new agricultura l productivity empowers rural industrial

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revitalization from three dimensions: “technology empowerment — industrial restructuring — factor activation”.
He points out that technology empowerment drives the shift from traditional to smart production, industrial
restructuring promotes the upgrade from single agriculture to i ntegration with the tertiary industry, and factor
activation turns idle resources into value. The takeaway for Yu xi is that if tech empowerment only stays at the
“technology” stage without also pushing forward “industrial restructuring” and “factor activation”, then efforts to
connect and support farmers will only remain at the basic level of rent and wages. Cai Jie et al. (2025) summarize,
f r o m a s y m b i o t i c p e r s p e c t i v e , f o u r m e c h a n i s m s — ” i n d u s t r y c h a i n extension, supply chain optimization, value
chain enhancement, and benefit chain connection”—which also sho w that the distribution of tech gains needs to
be aligned with the coordinated evolution of the industry, supp ly, and value chains[14]. Wei Zhixin et al. (2026),
using Yunnan flower cooperatives as an example, reveal a “rent + w a g e s + s h a r e s + b r a n d p r e m i u m + t e c h
trusteeship” model[22], which provides a reference framework for embedding technology in Yuxi's initiatives to
connect and support farmers.
5. Pathways for Coordinated Advancement of Classified Policies and Technology Empowerment
(1) Layered Precision Empowerment: Provincial Leadership, Municipal Support, County Foundation
The primary task of coordinated advancement is to match technol ogical supply with the level of the base, rather
than pushing all technologies to every base. Provincial-level bases should take on the role of demonstrating leading
technologies. Provincial bases selectively recommend municipal bases, and the criteria for recognition emphasize
breakthroughs such as “modern facilities and close farmer-integ rated mechanisms” For th ese bases, technology
empowerment should focus on cutting-edge technologies like smar t greenhouses, full-substrate cultivation, PLC
environmental control, germplasm innovation, and end-to-end digital traceability, making them “showcases” and
“testing grounds” for technologi cal routes. Bases like Chengjia ng Blueberry, Lvjulong Orchid, and Rongrong
Agriculture’s long-season chili already meet these conditions. The next step is to package their technical
parameters, cost structures, and output benefits into replicabl e “tech packages” for gradual transfer to municipal
and county bases.
City-level bases should take on the role of promoting integrated technologies. Since there are quite a few city-level
bases and they cover a full range of industry types, they act a s the middle layer for technology integration.
Empowering them should focus on a combined tech solution of “fa cilities + quality seeds + green pest control +
post-harvest processing”, rather than individual technologies. The Tonghai vegetable base group, Huaning citrus
base, and Xinping citrus base are suitable for this function. W e can rely on the nine provincial science and
technology task forces to set up “city-level base technology integration demonstration sites” according to industry.
Each task force pairs with several city-level bases to form a technical transfer chain of “expert team → city-level
base → county-level base”. This corresponds to “system-level” empowerment—cross-step technology integration.
County-level bases should take o n the role of spreading applica ble technologies. These bases are the most
numerous and varied, so tech support should focus on low-cost, easy-to-use, and quick-result techniques: green
pest control and crop rotation for open-field vegetables, water-saving irrigation and water-fertilizer integration for
mountain orchards, disease-free management and waste recycling for livestock, and simple cold chains and pre-
cooling at the field. Among the 39 demonstration bases in Tongh ai, the ones with lower scores, as well as the
planting and breeding bases in Yimen and Eshan, should be key targets for spreading these practical technologies.
County-level empowerment shouldn’t aim for “high-end and cuttin g-edge”, but rather for “coverage” and
“sustainability”. This correspond s to “operational-level” empow erment — replacing traditional practices with
single-piece technologies.
(2) Categorized Technical Routes: Facility Fruits and Vegetables, Open-field Vegetables, Flowers, Livestock and
Poultry, Processing and Distribution
The Yuxi base covers multiple types, including fruits, flowers, vegetables, Chinese medicinal materials, livestock
and poultry, and edible fungi, with significant differences in the technical logic of each industry. Chen Qiong et al.
(2026) summarized three types of technology empowerment models from the practice at Henan Academy of
Agriculture—intensive use of technological innovation resources, technology-driven improvement in quality and
efficiency of specialized advantageous industries, and technology aiding the integration of agriculture, culture, and
tourism—showing that technology empowerment needs to be differe ntiated according to industry type and base
function. Based on Y uxi's actual situation, five clear technical routes can be formed.
The technical approach for facility-grown fruits and vegetables (like Chengjiang blueberries, Jiangchuan
strawberries, Eshan bell peppers, etc.) is “facility upgrade—va riety adaptation—digital management—post-
harvest commercialization”. The focus is on turning technologie s such as full-substrate off-ground cultivation,
integrated water and fertilizer systems, intelligent temperature control, and waste liquid recovery into standardized

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modules to reduce the replication cost for county-level bases. At the same time, financial products like blueberry
loans and facility loans are provided to ease investment thresh old constraints. Wang Ying (2026) points out that
large-scale agricultural operato rs face strong constraints on t echnology adoption costs, and lowering adoption
barriers requires optimizing financing structures and promoting localized solutions. This insight is directly relevant
for the financial support of facility-grown fruit and vegetable bases [19].
The technical approach for open-field vegetables (like Tonghai vegetables, Jiangchuan vegetables, etc.) is “green
control—crop rotation and interplanting—cold chain precooling—e xport standards”. Tonghai vegetable exports
account for 92% of the county's total exports, and the focus of technological support isn't on greenhouses, but on
pesticide reduction, quality safety tracking, field precooling, and cold chain collection and distribution. The science
and technology task force should promote Tonghai's 11 sets of technical standards to similar bases.
The technical route for flower cultivation (flower bases in Hon gta District, Jiangchuan District, and Tonghai
County) is “seed industry innovation – facility cultivation – p ost-harvest handling – brand premium”. The
germplasm resources and virus-free seedlings of Jinhai Roses, L vjulong Phalaenopsis, and Y unxiu Flowers are
core technological assets, which should be distributed to city- and county-level flower bases through a “company

• research institute” joint breeding platform, along with cultivation standards. In the post-harvest stage, the focus
  should be on promoting vacuum pre-cooling, automatic grading, and coating preservation.
  The technical approach for lives tock and poultry (breeding base s in Hongta District, Yimen County, and Eshan
  County) is “breeding quality stock – disease purification – facility farming – recycling of manure”. Yuxi has quite
  a few pig and poultry bases, but their tech integration is less visible compared to crop farming. The focus should
  be on upgrading breeding farms, building disease-free animal fa rms, implementing multi-layer facility farming,
  and recycling manure, creating a circular link with the organic fertilizer needs of crop bases.
  The technical route for processing and circulation bases (Hongt a District, Tonghai County, Y uanjiang County
  processing bases) is “initial processing at the production site —deep processing—cold chain logistics—digital
  trading”. Bases like Tonghai Yang’s natural product pigment extraction, Y uanjiang mango processing, and Hongta
  District grain and oil processing should focus on connecting with agricultural product processing parks, cold chain
  distribution centers, and e-comme rce platforms, extending tech empowerment from the production side to the
  processing and circulation side. Wang Keshan and Ren Pidong (20 26) pointed out that artificial intelligence in
  agricultural industry chain and supply chain safety management needs to shift “from experience-based judgment
  to dynamic monitoring, from post-event remedies to pre-event pr evention, from local trade-offs to overall
  optimization, and from single-point management to system-wide c oordination”. This insight provides guidance
  for the digital upgrading of processing and circulation bases[24].
  (3) Building a Collaborative Mechanism: joint review coordinati on, special task force assignments, linking
  technical indicators with rewards instead of subsidies, digital platform monitoring.
  There needs to be an institutional interface between classification identification and technical matching; otherwise,
  they are hard to reconcile. Jin Lifu and Zhang Y uan (2026) pointed out that efficiently empowering new types of
  productivity requires continuously optimizing mechanism design in technology, talent, industry, and policy [16];
  Ma Defu and Yang Bohan (2026) emphasized “promoting deep integr ation of technology and industry through
  scenario-driven approaches, and optimizing governance and polic y supply through institutional innovation” [17].
  Considering the actual situation in Yuxi, we can start from four institutional interfaces.
  First, establish a coordinated review mechanism between base re cognition and science and technology projects.
  The Yuxi plan has already specified that the Municipal Agricult ure and Rural Affairs Bureau will take the lead,
  together with relevant municipal departments, to set up a base construction review mechanism. However, the
  review currently mainly serves recognition and recommendation purposes and hasn’t yet been integrated with the
  allocation of science and technology projects. It’s suggested t o involve science and technology departments, the
  Agricultural Science Academy, and Yuxi Agricultural V ocational and Technical College in the reviews, so that for
  bases proposed for recognition or upgrading, a “technical needs list” can be created at the same time. This would
  serve as a basis for sending tech nology task forces, project ap plications, and facility subsidies later on. County-
  level base databases in Jiangchuan District, Yimen County, and Tonghai County can be used as pilots to first create
  a “one base, one technical file” system.
  Second, implement a targeted service approach by science and te chnology task forces. Nine provincial-level
  science and technology task forces, with over 200 experts, should be assigned to specific industries and counties.
  Each task force should work with 1–2 city-level base clusters a nd several county-level bases, expanding their
  services from just “technical training” to the full process: “technical diagnosis—plan design—demonstration and
  promotion—effect evaluation”. The three-year service model of t he Tonghai Vegetable Science and Technology

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Task Force (29 experts, 11 new varieties, 11 sets of technical standards, 200 acres of co re zones, 1,000 acres of
demonstration plots, 65,600 acres of promotion) can serve as a template for this targeted service. The assessment
of task force members should shift from “number of services pro vided” to “improvement in base technical
indicators”.
Third, include technical indicators as conditions for reward-based subsidies. Currently, reward-based subsidies are
mainly used for infrastructure improvement, promotion of production technology, and product quality control, but
the subsidy conditions focus more on the “recognition level” ra ther than “technological upgrades”. It's
recommended to set technical thresholds for city-level and above bases to qualify for subsidies: indicators such as
facility coverage, high-quality s eed coverage, green pest contr ol coverage, post-harvest commercialization rate,
and digital management coverage must meet agreed standards to r eceive subsidies. For provincial and city-level
bases that complete technological upgrades and drive county-level bases, additional rewards should be given. This
can turn “classified recognition” into “classified incentives”, allowing technology empowerment to leverage fiscal
support. Zhou Yuzhong et al. (2026) suggested when discussing t echnology-financed support for leading
agricultural tech companies to “establish a long-term funding supply system, build a full lifecycle service system,
and improve supporting risk management systems”, and this appro ach is similarly informative for managing
reward-based subsidy funds [24].
Fourth, build a digital monitoring platform for base classifica tion and tech empowerment. Relying on existing
platforms like the Yuxi National Agricultural Science and Technology Park, Hongta District Flower Big Data, and
Huaning Citrus Smart Agriculture, establish a “classification–technology” database covering bases at provincial,
city, and county levels. This database will dynamically record indicators such as industry type, certification level,
facility standards, use of quality seeds, technical training, a nd farmer support. The platf orm's aim isn’t to create
another information system but to provide technical demand signals for classification, a basis for tech allocation,
and a reference for dynamic management decisions. Pilot project s can first run in the four industry zones of
Chengjiang blueberries, Tonghai vegetables, Huaning citrus, and Xinping citrus, then expand to livestock and
poultry, traditional Chinese medicine, and edible fungi. Li Xia oning (2026) pointed out that empowering new
agricultural productivity with the digital economy requires “re shaping decision-making through data elements,
driving production upgrades through tech integration, and recon structing the industry value chain via platform
economy”. The base digital monitoring platform is exactly a con crete tool for reshaping classification decisions
through data elements[25].
(4) Integrating Technology with Supporting Farmers: Keeping the Benefits within the Base
The coordination between targeted measures and technological em powerment ultimately needs to translate into
increased income for farmers. The “315” model for blueberries i n Chengjiang and the “125” model for citrus in
Xinpings provide two approaches: the former ties technological benefits to village collectives and farmers through
systems like rent, service fees, and management fees, while the latter links technology transfer to farmer income
through production-based management and menu-style service mana gement. Han Guihua's (2026) “Technology
Empowerment–Industry Reconstruction–Resource Activation” framew ork suggests that supporting farmers
shouldn't just stop at technology empowerment, but should also push forward industry restructuring and resource
activation at the same time [21]. Cai Jie et al. (2025) outline four mechanisms—“extending the industrial chain,
optimizing the supply chain, upgrading the value chain, and con necting the benefit chain”—providing guidance
for designing mechanisms to integrate technology in supporting farmers[14]. The “rent + salary + equity + brand
premium + technical management” model proposed by Wei Zhixin et al. (2026) can directly serve as a reference
for upgrading systems to support farmers in Yuxi's flower, vegetable, and fruit bases[22].
Specifically, in the production stage, the technical plans from science and technology envoys and teams should
clearly define what parts can be operated by farmers and what parts are handled by companies or cooperatives, to
avoid the plan only being suitable for large-scale entities. In the processing and circulation stage, technologies like
on-farm pre-cooling, grading and packaging, and e-commerce live streaming should be open to cooperatives and
village collectives, lowering the barrier for farmers to partic ipate. In the profit-sharin g stage, including tech
management, order empowerment, and brand premium in the agreements linking farmers and businesses ensures
that farmers not only get rent and wages but also can share in the added value from technological upgrades. In
Tonghai’s 39 demonstration bases evaluation form, the “farmer linkage mechanism” isn’t listed separately yet. It’s
suggested to add verifiable indicators like “number of farmers driven by technology”, “area under tech
management”, and “order purchase ratio” in the city-level and county-level recognition standards.
6. Conclusions and Discussion
This article focuses on the plat eau specialty agriculture base in Yuxi City, examining the coordination between

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targeted policies and technological empowerment, and comes to three main conclusions.
First, Yuxi already has the institutional foundation and practical experience for coordinating targeted policies and
technological empowerment. The three-level base recognition sys tem, the quantitative scoring with the “Ten
Standards”, dynamic management, and incentive-based subsidies form the structural framework for classification;
facilities agriculture, seed industry, science and technology s pecialists, digital platforms, and processing cold
chains make up the five-dimensional supply of technological emp owerment; bases like Chengjiang Blueberry,
Rongrong Agriculture, Tonghai Vegetables, and Lvjulong Orchids have already shown an initial coupling of “high
facilities—high output—high impact”.
Second, the bottleneck in collaborative progress isn’t in a sin gle link, but in the lack of a stable institutional
interface between classification recognition and technology matching. The evaluation criteria lean heavily on static
conditions, there’s a mismatch between technology supply and base types, county-level bases have weak capacity,
and the technology penetration in connecting and supporting far mers is insufficient. These four factors reinforce
each other, making it hard for the “recognized bases” and “empo wered bases” to fully overlap. As Jin Lifu and
Zhang Yuan (2026) mentioned, the dilemma of “being empowered but unable to deliver”[16], and as Ma Defu and
Yang Bohan (2026) summarized, the issues of “infrastructure and technology application gaps, talent shortages
and capability gaps, shallow technology-to-industry integration , and incomplete institutional and policy support
systems” [17]are all reflected to some extent at the Yuxi base level.
Third, the collaborative approach should be based on four dimensions: “hierarchy—categorization—mechanism—
linking farmers”: provincial bases lead with demonstrations of cutting-edge technologies, municipal bases handle
the promotion of integrated technologies, and county bases popularize applicable technologies; different technical
routes are followed for facility vegetables and fruits, open-fi eld vegetables, flowers, livestock and poultry, and
processing and circulation; institutional interfaces are formed through joint review mechanisms, designated teams
covering specific areas, linking technical indicators with rewa rds instead of subsidies, and digital platform
monitoring; in the step of connecting and helping farmers, the benefits of the technologies are kept within the
bases.
The limitation of this article is that the material is mainly b ased on public documents and case reports, and does
not yet use micro-level panel data at the base level, so the ca usal relationship of “hier archical categorization—
technology input—output benefits ” can only be inferred mechanis tically rather than strictly identified. Future
research could rely on the Yuxi city base database and records of science and technology commissioners’ services
to build matched data at the bas e level and test the heterogene ous effects of hierarchical empowerment and
categorized technical routes on per-acre yield, resource efficiency, and farmers’ income; the analytical framework
could also be extended to other cities in Yunnan to compare differences in categorized policy implementation and
collaborative technology empowerment models under different resource endowments and policy intensities.
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Notes
Note 1. See the notice from the Yuxi Municipal Committee Office of the CPC and the Yuxi Municipal People's
Government Office on issuing the '”Implementation Plan for Accelerating the Construction of Modern Agricultural
Industry Bases in Yuxi City”.https://www.yuxi.gov.cn/yxszfxxgk/zcjd1957/20231113/1489189.html

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